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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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with substantial research experience will be highly advantageous. Experience in computer programming will be essential. Studentships are open to home students only. The deadline to have completed and
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. This project will focus on developing the quantum control building blocks for implementing low-overhead quantum error correction on trapped ions-based quantum processors. Quantum control techniques can open
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maintain existing analysis/sorting equipment and computer systems. Participate in the selection of new facility equipment and software with advancing technology so that the facility maintains its status as a
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research network Your profile Master’s degree (or equivalent) in a quantitative discipline, Earth system/environmental sciences or engineering, physics, mathematics/statistics, computer/data science
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supported by an ARC Industry Fellowship, in partnership with Bush Heritage Australia. The student will work closely with ecologists and computer scientists at QUT and conservation managers at Bush Heritage
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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, for instance, utilise conversational agents, computer vision, mixed reality, wearables etc. Disability, Technology, and Society: Research with a sociological or anthropological focus on the use of bespoke and/or
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5